from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


SCREAMING_SNAKE_CASE__		:       str       						=       {
    "configuration_layoutlmv3": [
        "LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "LayoutLMv3Config",
        "LayoutLMv3OnnxConfig",
    ],
    "processing_layoutlmv3": ["LayoutLMv3Processor"],
    "tokenization_layoutlmv3": ["LayoutLMv3Tokenizer"],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE__		:       int       						=       ["LayoutLMv3TokenizerFast"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE__		:       Dict       						=       [
          "LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST",
          "LayoutLMv3ForQuestionAnswering",
          "LayoutLMv3ForSequenceClassification",
          "LayoutLMv3ForTokenClassification",
          "LayoutLMv3Model",
          "LayoutLMv3PreTrainedModel",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE__		:       Any       						=       [
          "TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST",
          "TFLayoutLMv3ForQuestionAnswering",
          "TFLayoutLMv3ForSequenceClassification",
          "TFLayoutLMv3ForTokenClassification",
          "TFLayoutLMv3Model",
          "TFLayoutLMv3PreTrainedModel",
      ]

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE__		:       List[str]       						=       ["LayoutLMv3FeatureExtractor"]
      SCREAMING_SNAKE_CASE__		:       List[str]       						=       ["LayoutLMv3ImageProcessor"]


if TYPE_CHECKING:
      from .configuration_layoutlmva import (
          LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP,
          LayoutLMvaConfig,
          LayoutLMvaOnnxConfig,
      )
      from .processing_layoutlmva import LayoutLMvaProcessor
      from .tokenization_layoutlmva import LayoutLMvaTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_layoutlmva import (
                LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
                LayoutLMvaForQuestionAnswering,
                LayoutLMvaForSequenceClassification,
                LayoutLMvaForTokenClassification,
                LayoutLMvaModel,
                LayoutLMvaPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_layoutlmva import (
                TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFLayoutLMvaForQuestionAnswering,
                TFLayoutLMvaForSequenceClassification,
                TFLayoutLMvaForTokenClassification,
                TFLayoutLMvaModel,
                TFLayoutLMvaPreTrainedModel,
            )

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor
            from .image_processing_layoutlmva import LayoutLMvaImageProcessor

else:
      import sys

      SCREAMING_SNAKE_CASE__		:       Any       						=       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




A						=			'\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

A						=			[{'type': 'code', 'content': INSTALL_CONTENT}]
A						=			{
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}